Error when predicting U-Net masks : Can't parse 'dsize'. Input argument doesn't provide sequence protocol

I am glad to say that I have managed to train a U-Net model. However, I get an error when trying to predict the masks. Please have a look at the code below. This relates to this question where the training part could be found.

Code(Predicting Part):

#define augmentations 
inference_transform = A.Compose([
    A.Resize(256, 256, always_apply=True),
    A.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)), 
    ToTensorV2()
])
​
#define function for predictions
def predict(model, img, device):
    model.eval()
    with torch.no_grad():
        images = img.to(device)
        output = model(images)
        predicted_masks = (output.squeeze() >= 0.5).float().cpu().numpy()
        
    return(predicted_masks)
​
#define function to load image and output mask
def get_mask(img_path):
    image = cv2.imread(img_path)
    #assert image is not None
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    original_height, original_width = tuple(image.shape[:2])
    
    image_trans = inference_transform(image = image)
    image_trans = image_trans["image"]
    image_trans = image_trans.unsqueeze(0)
    
    image_mask = predict(unet, image_trans, device)
    #image_mask = image_mask.astype(np.int16)
    image_mask = cv2.resize(image_mask, original_height, original_width, 
                          interpolation=cv2.INTER_NEAREST)
        
    return(image_mask)

############################

#image example
example_path = "../input/test-image/10078.tiff"
image = cv2.imread(example_path)
#assert image is not None
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

mask = get_mask(example_path)

masked_img = image*np.expand_dims(mask, 2).astype("uint8")

#plot the image, mask and multiplied together
fig, (ax1, ax2, ax3) = plt.subplots(3)

ax1.imshow(image)
ax2.imshow(mask)
ax3.imshow(masked_img)

Output:

---------------------------------------------------------------------------
error                                     Traceback (most recent call last)
/tmp/ipykernel_18/2666594668.py in <module>
      5 image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
      6 
----> 7 mask = get_mask(example_path)
      8 
      9 masked_img = image*np.expand_dims(mask, 2).astype("uint8")

/tmp/ipykernel_18/1641483929.py in get_mask(img_path)
     30     image_mask = image_mask.astype(np.int16)
     31     image_mask = cv2.resize(image_mask, original_height, original_width, 
---> 32                           interpolation=cv2.INTER_NEAREST)
     33 
     34     return(image_mask)

error: OpenCV(4.5.4) :-1: error: (-5:Bad argument) in function 'resize'
> Overload resolution failed:
>  - Can't parse 'dsize'. Input argument doesn't provide sequence protocol
>  - Can't parse 'dsize'. Input argument doesn't provide sequence protocol

Would anyone be able to help me in this regards please?

Thanks & Best Regards Schroter Michael